Highly parallel computer architectures provide the only means to attain the computational rates demanded by advanced biomedical computing problems. The goals of the Highly Parallel Biomedical Computing Project are to determine which parallel architectures are best for the classes of problems that arise in biomedical computing, to develop parallel algorithms for advanced biomedical computing problems, and to provide a high-performance parallel computer facility that will benefit the NIH staff in their scientific computing needs. CSL is investigating the following significant parallel computing issues in the context of computationally demanding biomedical applications: partitioning a problem into many parts that can be independently executed on different processors, designing algorithms so that delays of interprocessor communication can be kept to a small fraction of the computation time, designing the parts so that the computing load can be distributed evenly over the available processors, and designing algorithms so that the number of processors is a parameter and the algorithms can be configured dynamically. With its collaborators, CSL is developing and implementing parallel algorithms for the following biomedical application areas: Image Processing of Electron Micrographs in Structural Biology, Protein and Nucleic Acid Sequence Analysis, Nuclear Magnetic Resonance Spectroscopy, X-ray Crystallography, Protein Folding Prediction, Molecular Dynamics Simulations, Quantum Chemical Methods, and Medical Imaging. During the past year, CSL installed a 128 processor DARPA Touchstone Gamma Prototype parallel computer with a ten Gigabyte Concurrent I/O File System that was constructed by the Intel Supercomputer systems Division. Parallel algorithms were implemented to perform the computationally-intensive steps in the three-dimensional reconstruction of large icosahedral viruses from electron micrographs and to calculate the solvent accessible surface area of a protein that is used to determine the conformation of these macromolecules. In the coming year, work will continue in the application areas listed above.